多旋翼微型飞行器结构健康监测

P. Misra, Gopi Kandaswamy, Pragyan Mohapatra, Kriti Kumar Balamuralidhar, Prasant Misra Gopi Kandaswamy, Kriti Kumar
{"title":"多旋翼微型飞行器结构健康监测","authors":"P. Misra, Gopi Kandaswamy, Pragyan Mohapatra, Kriti Kumar Balamuralidhar, Prasant Misra Gopi Kandaswamy, Kriti Kumar","doi":"10.1145/3213526.3213531","DOIUrl":null,"url":null,"abstract":"Structural Health Monitoring (SHM) is a key troubleshooting methodology for assessing the working condition and health of (manned or unmanned) aerial vehicles; however, its understanding with respect to the multi-rotor class of Micro Aerial Vehicles (MAV) is limited. The portentous structural failure sources, in this case, are the two moving components: motors and propellers. In this paper, we undertake a detailed exercise of characterizing the common and frequent faults of these units using multi-modal sensing of vibration, acoustic noise, input power, and thrust profiles; and then use relevant features to perform a two-level diagnosis. Through our empirical fault studies on our custom designed test rig, we propose a set of befitting features in each sensory domain; which result in high fault detection and classification accuracy that exceeds 90%.","PeriodicalId":237910,"journal":{"name":"Proceedings of the 4th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Structural Health Monitoring of Multi-Rotor Micro Aerial Vehicles\",\"authors\":\"P. Misra, Gopi Kandaswamy, Pragyan Mohapatra, Kriti Kumar Balamuralidhar, Prasant Misra Gopi Kandaswamy, Kriti Kumar\",\"doi\":\"10.1145/3213526.3213531\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Structural Health Monitoring (SHM) is a key troubleshooting methodology for assessing the working condition and health of (manned or unmanned) aerial vehicles; however, its understanding with respect to the multi-rotor class of Micro Aerial Vehicles (MAV) is limited. The portentous structural failure sources, in this case, are the two moving components: motors and propellers. In this paper, we undertake a detailed exercise of characterizing the common and frequent faults of these units using multi-modal sensing of vibration, acoustic noise, input power, and thrust profiles; and then use relevant features to perform a two-level diagnosis. Through our empirical fault studies on our custom designed test rig, we propose a set of befitting features in each sensory domain; which result in high fault detection and classification accuracy that exceeds 90%.\",\"PeriodicalId\":237910,\"journal\":{\"name\":\"Proceedings of the 4th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 4th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3213526.3213531\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3213526.3213531","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

结构健康监测(SHM)是评估(有人或无人)飞行器工作状态和健康的关键故障诊断方法;然而,对于多旋翼类微型飞行器(MAV)的理解有限。在这种情况下,潜在的结构故障来源是两个运动部件:发动机和螺旋桨。在本文中,我们采用振动、噪声、输入功率和推力剖面的多模态传感对这些单元的常见和频繁故障进行了详细的表征;然后利用相关特征进行两级诊断。通过对我们定制设计的试验台的经验故障研究,我们提出了一套适合于每个感官域的特征;从而实现了高的故障检测和分类准确率超过90%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structural Health Monitoring of Multi-Rotor Micro Aerial Vehicles
Structural Health Monitoring (SHM) is a key troubleshooting methodology for assessing the working condition and health of (manned or unmanned) aerial vehicles; however, its understanding with respect to the multi-rotor class of Micro Aerial Vehicles (MAV) is limited. The portentous structural failure sources, in this case, are the two moving components: motors and propellers. In this paper, we undertake a detailed exercise of characterizing the common and frequent faults of these units using multi-modal sensing of vibration, acoustic noise, input power, and thrust profiles; and then use relevant features to perform a two-level diagnosis. Through our empirical fault studies on our custom designed test rig, we propose a set of befitting features in each sensory domain; which result in high fault detection and classification accuracy that exceeds 90%.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信